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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Carbon-efficient conversion of natural gas and natural-gas condensates to chemical products and intermediate feedstocks via catalytic metal–organic framework (MOF) chemistry

The net-zero carbon emission scenario of stopping hydrocarbon use as fuel is unlikely to end the extraction of fossil hydrocarbons. Remaining will be a sizable need for hydrocarbons as feedstocks for commodity chemicals destined for transformation into polymers, manufacturing-relevant intermediates, and value-added chemicals. Historically, the primary feedstock source has been oil. Over the past dozen years, however, fracking-based extraction of shale-trapped natural gas from known enormous reserves, in North America, has resulted in feedstock sourcing instead from wet shale gas. This shift has transformed the catalytic chemistry of commodity chemical manufacturing. In this paper, following a brief discussion of the merits and limitations of crystallographically well-defined metal–organic frameworks (MOFs) as model catalysts and catalyst-supports, we examined their applications for understanding and potentially enabling carbon-economical, catalytic transformation of C 1 , C 2 , C 3 , and C 4 components of natural gas to desirable commodity chemicals, intermediates, or model compounds.

03 NATURAL GAS↗
DOE OSTI2021

Towards additive manufacturing of magnetocaloric working materials

The feasibility of three-dimensional printing via the Directed Energy Deposition (DED) technique is demonstrated for the ferromagnetic AlFe 2 B 2 (aka 1-2-2) compound, which shows promise as a working material for room-temperature magnetocaloric devices. Like many intermetallic materials, the 1-2-2 compound is brittle at room temperature; not only is it difficult to synthesize from the melt, it is challenging to form it into useful geometries necessary for effective heat transfer in magnetocaloric devices. Using Laser Engineered Net Shaping (LENS TM ) synthesis from two powder precursors, AlB 2 and Fe, samples of simple (rod) and complex (honeycomb) architectures were successfully synthesized. Furthermore, the phase constitution and distribution, magnetic transition temperature, and saturation magnetization determined for the LENS TM -synthesized rod sample are all similar to those obtained for 1-2-2 materials made by conventional casting. Further, the measured magnetic entropy change, as determined from Maxwell's Relations applied to magnetic data, indicates that the magnetocaloric response of the annealed LENS TM -printed rod samples are comparable to those of the 1-2-2 compounds made by conventional techniques. These results confirm that complex magnetofunctional shapes, which are needed for efficient energy conversion in magnetocaloric devices, can be rapidly fabricated from the AlFe 2 B 2 compound.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Extended defects in GaAs/GaAs 1-x Sb x /GaAs (001) heterostructures

The atomic-scale structure of extended defects in GaAs/GaAs 1-x Sb x /GaAs (001) heterostructures has been characterized using aberration-corrected scanning transmission electron microscopy. The defect located at the tensile-strained GaAs(cap)/GaAs 0.34 Sb 0.66 interface had no edge component in the projection plane and is identified as either a dissociated screw dislocation or a partial dislocation dipole. The associated intrinsic stacking fault is bounded by two 30° Shockley partial dislocations of opposite sign. Another defect, located at the compressively-strained GaAs 0.91 Sb 0.09 /GaAs(substrate) interface, is identified as a dissociated 90° dislocation. The associated intrinsic stacking fault is bounded by a 30° Shockley partial dislocation and a partial dislocation with a Burgers vector of either or , where a is the lattice constant. Unpaired atomic columns observed at the cores of the 30° Shockley partial dislocations indicate that both defects belong primarily to the glide set.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Evaluation of Equiatomic CrMnFeCoNiCu System and Subsequent Derivation of a Non-Equiatomic MnFeCoNiCu Alloy

Investigation into non-equiatomic high-entropy alloys has grown in recent years due to questions about the role of entropy stabilization in forming single-phase solid solutions. Non-equiatomic alloys have been shown to retain the outstanding mechanical properties exhibited by their equiatomic counterparts and even improve electrical, thermal, and magnetic properties, albeit with relaxed composition bounds. However, much remains to understand the processing–structure–property relationships in all classes of so-called high-entropy alloys (HEAs). Here, we are motivated by the natural phenomena of crystal growth and equilibrium conditions to introduce a method of HEA development where controlled processing conditions determine the most probable and stable composition. This is demonstrated by cooling an equiatomic CrMnFeCoNiCu alloy from the melt steadily over 3 days (cooling rate ~4 °C/h). The result is an alloy containing large Cr-rich precipitates and an almost Cr-free matrix exhibiting compositions within the MnFeCoNiCu system (with trace amounts of Cr). From this juncture, it is argued that the most stable composition is within the CrMnFeCoNiCu system rather than the CrMnFeCoNi system. With further optimization and evaluation, a unique non-equiatomic alloy, Mn 17 Fe 21 Co 24 Ni 24 Cu 14 , is derived. The alloy solidifies and recrystallizes into a single-phase face-centered cubic (FCC) polycrystal. In addition to possible applications where Invar is currently utilized, this alloy can be used in fundamental studies that contrast its behavior with its equiatomic counterpart and shed light on the development of HEAs.

36 MATERIALS SCIENCE↗
DOE OSTI2019

Nitrogen-dependent coordination of cell cycle, quiescence and TAG accumulation in Chlamydomonas

Abstract Microalgae hold great promises as sustainable cellular factories for the production of alternative fuels, feeds, and biopharmaceuticals for human health. While the biorefinery approach for fuels along with the coproduction of high-value compounds with industrial, therapeutic, or nutraceutical applications have the potential to make algal biofuels more economically viable, a number of challenges continue to hamper algal production systems at all levels. One such hurdle includes the metabolic trade-off often observed between the increased yields of desired products, such as triacylglycerols (TAG), and the growth of an organism. Initial genetic engineering strategies to improve lipid productivity in microalgae, which focused on overproducing the enzymes involved in fatty acid and TAG biosynthesis or inactivating competing carbon (C) metabolism, have seen some successes albeit at the cost of often greatly reduced biomass. Emergent approaches that aim at modifying the dynamics of entire metabolic pathways by engineering of pertinent transcription factors or signaling networks appear to have successfully achieved a balance between growth and neutral lipid accumulation. However, the biological knowledge of key signaling networks and molecular components linking these two processes is still incomplete in photosynthetic eukaryotes, making it difficult to optimize metabolic engineering strategies for microalgae. Here, we focus on nitrogen (N) starvation of the model green microalga, Chlamydomonas reinhardtii , to present the current understanding of the nutrient-dependent switch between proliferation and quiescence, and the drastic reprogramming of metabolism that results in the storage of C compounds following N starvation. We discuss the potential components mediating the transcriptional repression of cell cycle genes and the establishment of quiescence in Chlamydomonas, and highlight the importance of signaling pathways such as those governed by the target of rapamycin (TOR) and sucrose nonfermenting-related (SnRK) kinases in the coordination of metabolic status with cellular growth. A better understanding of how the cell division cycle is regulated in response to nutrient scarcity and of the signaling pathways linking cellular growth to energy and lipid homeostasis, is essential to improve the prospects of biofuels and biomass production in microalgae.

09 BIOMASS FUELS↗
DOE OSTI2025

First-Principles-Based Study of the Decomposition of Phenol and Hydroquinone on Pt(111) Combined with Quantitative Information from XPS Spectra to Address the Impact of Coverage and Number of Hydroxyl Functional Groups

A combined first-principles-based and experimental X-ray photoelectron spectroscopy approach was used to investigate the thermal decomposition of two model biofuel compounds, phenol and hydroquinone, on Pt(111) at both low and high coverages. The DFT-based approach yields adsorption geometries and energies, activation barriers and core-level binding energy shifts for C 1s and O 1s. Increasing the coverage in the theoretical model leads to slight shifts in core-level binding energies─toward higher values for C 1s and lower values for O 1s. It also alters the energy profiles of the decomposition reaction pathway, resulting in weaker adsorption energies and changes in both reaction and activation barriers. At low temperatures, we observe a multilayer for phenol and hydroquinone upon adsorption, with desorption occurring at 200 and 270 K, respectively. Following desorption of the multilayer, decomposition proceeds via initial O–H bond scission, followed by two parallel pathways involving either C–H or C–C bond scission, whereby in the case of phenol C–H bond scission occurs first. Here, we further provide characteristic core level binding energies by theoretical calculations that are subsequently used in experimental analyses, establishing a reference database for key spectra of phenolic functionalities applicable to a range of catalytic reactions.

09 BIOMASS FUELS↗
DOE OSTI2024

c-HAND: near real-time coastal flood mapping

The Texas Gulf Coast region contains significant centers of population, infrastructure, and economy and is threatened by intensifying tropical storms. The flooding from these tropical storms often has multiple compounding drivers. This characteristic presents a complex numerical problem where a simulation must consider multiple hydrologic forcings. While several procedures exist for addressing this problem numerically, they tend to be resource-intensive and cannot be conducted in near real-time. We extend GeoFlood, a reduced physics approach for fluvial flood forecasting, to rapidly predict coastal and compound fluvial-coastal inundation. This method is validated against a numerical ocean circulation model (ADCIRC) simulation of Hurricane Ike, a major coastal flooding event that happened on the Texas Gulf Coast in 2008. We show that the inundation map generated by coastal HAND (c-HAND) has reasonable agreement with the ADCIRC simulation while taking about 1.7% of the time currently needed to run ADCIRC on a supercomputer. While our model correctly predicts 99% of ADCIRC-inundated DEM cells, it also overpredicts inundated area by a factor of approximately 27%. We combine c-HAND with the GeoFlood framework for fluvial flood forecasting to create a compound fluvial-coastal inundation mapping workflow that can be run in near real-time. c-HAND's fast wall-clock time and low CPU requirements can support decision making by first response personnel. The method provides timely and convenient access to crucial information, such as the locations of flooded roads and inundated coastal areas.

42 ENGINEERING↗
DOE OSTI2020

TAILORED BIOBLENDSTOCKS WITH LOW ENVIRONMENTAL IMPACT TO OPTIMIZE MCCI ENGINES

The overall objective of the project is to develop and demonstrate a microalgae bio-blendstock with greater than 60% greenhouse gas reduction potential relative to petroleum diesel, that can reduce sooting propensity, increase cetane number and improve engine thermal efficiency relative to a baseline diesel engine operating on conventional fuel. Specific objectives include: (1) development of a new framework for both LCA and TEA that explicitly considers temporal variation in productivity and the frequency of crop loss; (2) determination of how fuel compounds that can be produced from the algal biomass can be ‘bio-tailored’ based on the species composition and biological production process, and subsequent processing via HTL to biocrude, and upgrading of the biocrude; (3) execution of a feedback loop (algae production  biocrude refining  combustion optimization  feedback to refining stage), for optimization of fuels for MCCI combustion; (4) optimization of MCCI combustion and emissions performance, accounting first for the biological processes that dictate the chemical composition of biocrude oil, and second for the subsequent chemical processes that comprise mixing controlled compression ignition combustion; (6) simulation of MCCI engine combustion processes to demonstrate the incorporation of relevant fuel chemistry that captures the specific impacts of optimized algal fuels.

09 BIOMASS FUELS↗
DOE OSTI2020

Tailored Bioblendstocks with Low Environmental Impact to Optimize MCCI Engines

The overall objective of the project is to develop and demonstrate a microalgae bio-blendstock with greater than 60% greenhouse gas reduction potential relative to petroleum diesel, that can reduce sooting propensity, increase cetane number and improve engine thermal efficiency relative to a baseline diesel engine operating on conventional fuel. Specific objectives include: (1) development of a new framework for both LCA and TEA that explicitly considers temporal variation in productivity and the frequency of crop loss; (2) determination of how fuel compounds that can be produced from the algal biomass can be ‘bio-tailored’ based on the species composition and biological production process, and subsequent processing via HTL to biocrude, and upgrading of the biocrude; (3) execution of a feedback loop (algae production  biocrude refining  combustion optimization  feedback to refining stage), for optimization of fuels for MCCI combustion; (4) optimization of MCCI combustion and emissions performance, accounting first for the biological processes that dictate the chemical composition of biocrude oil, and second for the subsequent chemical processes that comprise mixing controlled compression ignition combustion; (6) simulation of MCCI engine combustion processes to demonstrate the incorporation of relevant fuel chemistry that captures the specific impacts of optimized algal fuels.

09 BIOMASS FUELS↗
DOE OSTI2026

Model data for infrastructure-aware simulation of compound flooding at Alligator Bayou Watershed, southeast Texas

This dataset supports infrastructure-aware hydrologic modeling and flood scenario analysis for the Alligator Bayou Watershed, a highly managed urban watershed in Southeast Texas. It includes Jupyter notebooks for figure reproduction, model configuration files, simulation outputs, and derived products used to quantify the influence of engineered stormwater infrastructure on flood behavior across multiple spatial scales. The dataset was generated using the Watershed Workflow Python package and the Advanced Terrestrial Simulator (ATS), enabling integrated surface–subsurface hydrologic simulations on a channel-aligned mesh with explicit representations of pump stations, gate structures, detention basins, and impervious surfaces. Outputs include time series of gate and pump flows, stage observations, and water balance components, as well as spatially explicit fields of peak ponded depth and flood duration across multiple infrastructure scenarios spanning a single-location detention basin expansion, distributed drainage limitations, and compound coastal flooding. These data facilitate full reproducibility of the manuscript figures and support further research on urban flood dynamics and the role of stormwater infrastructure in shaping watershed-scale flood response.

EARTH SCIENCE > OCEANS > COASTAL PROCESSES↗
DOE OSTI2021

Tailored Bioblendstocks With Low Environmental Impact To Optimize MCCI Engines

This project seeks to overcome impediments to expansion of algae cultivation and conversion into fuels to displace petroleum and reduce greenhouse gas (GHG) emissions. The overall objective of the project is to develop and demonstrate a microalgae bio-blendstock with greater than 60% greenhouse gas reduction relative to petroleum diesel, reduce sooting propensity, increase cetane number, improve engine thermal efficiency relative to a baseline diesel engine operating on conventional fuel. These objectives are being accomplished by: Applying cultivation of algae polycultures to achieve robustness and productivity, Converting whole algae to bio-hydrocarbons via Hydrothermal Liquefaction (HTL) to make a biocrude and up-grading the biocrude via hydroprocessing to obtain tailored bioblendstocks for diesel fuel, Optimizing diesel (MCCI) combustion through blending model compounds into diesel fuel to represent the tailored bioblendstocks through experiments and numerical simulation.

09 BIOMASS FUELS↗
DOE OSTI2021

Latent map Gaussian processes for mixed variable metamodeling

Gaussian processes (GPs) are ubiquitously used in sciences and engineering as metamodels. Standard GPs, however, can only handle numerical or quantitative variables. Here we introduce latent map Gaussian processes (LMGPs) that inherit the attractive properties of GPs and are also applicable to mixed data which have both quantitative and qualitative inputs. The core idea behind LMGPs is to learn a continuous, low-dimensional latent space or manifold which encodes all qualitative inputs. To learn this manifold, we first assign a unique prior vector representation to each combination of qualitative inputs. We then use a low-rank linear map to project these priors on a manifold that characterizes the posterior representations. As the posteriors are quantitative, they can be directly used in any standard correlation function such as the Gaussian or Matern. Hence, the optimal map and the corresponding manifold, along with other hyperparameters of the correlation function, can be systematically learned via maximum likelihood estimation. Through a wide range of analytic and real-world examples, we demonstrate the advantages of LMGPs over state-of-the-art methods in terms of accuracy and versatility. In particular, we show that LMGPs can handle variable-length inputs, have an explainable neural network interpretation, and provide insights into how qualitative inputs affect the response or interact with each other. We also employ LMGPs in Bayesian optimization and illustrate that they can discover optimal compound compositions more efficiently than conventional methods that convert compositions to qualitative variables via manual featurization.

42 ENGINEERING↗
DOE OSTI2021

Incorporation of sensing modalities into de novo designed fluorescence-activating proteins

Through the efforts of many groups, a wide range of fluorescent protein reporters and sensors based on green fluorescent protein and its relatives have been engineered in recent years. Here we explore the incorporation of sensing modalities into de novo designed fluorescence-activating proteins, called mini-fluorescence-activating proteins (mFAPs), that bind and stabilize the fluorescent cis -planar state of the fluorogenic compound DFHBI. We show through further design that the fluorescence intensity and specificity of mFAPs for different chromophores can be tuned, and the fluorescence made sensitive to pH and Ca 2+ for real-time fluorescence reporting. Bipartite split mFAPs enable real-time monitoring of protein–protein association and (unlike widely used split GFP reporter systems) are fully reversible, allowing direct readout of association and dissociation events. The relative ease with which sensing modalities can be incorporated and advantages in smaller size and photostability make de novo designed fluorescence-activating proteins attractive candidates for optical sensor engineering.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Cell-Free-Based Thermophilic Biocatalyst for the Synthesis of Amino Acids from One-Carbon Feedstocks

Bioproduction from one-carbon compounds, such as formate, is an attractive prospect due to reduced energy requirements and the possibility for using CO 2 as a sustainable feedstock. Formate-fixing pathways engineered using Escherichia coli lysate-based cell-free expression (CFE) biocatalysts have the potential to route 100% of feedstock carbon toward chemical synthesis but are undermined by siphoning of in-pathway metabolites and cofactors by the CFE background metabolism. To address this limitation, we engineer a CFE-based thermophilic multienzyme biocatalyst for the synthesis of serine and glycine from formate, bicarbonate, and ammonia. After expression of the thermophilic formate-to-serine pathway in a one-pot reaction, the mesophilic E. coli CFE background machinery is removed by simple heat denaturation, eliminating the siphoning of cofactors, inpathway metabolites, and products. After bioprocess optimization, including pathway gene expression duration and chemical synthesis temperature, we achieve near stoichiometric conversion of formate and bicarbonate to serine and glycine, reaching 97% of stoichiometric yield. The use of a moderately thermophilic biocatalyst allowed chemical synthesis to take place at mesophilic temperatures, enabling the balance of optimal enzyme activity with minimal metabolite/cofactor thermal degradation. In a fed-batch experiment, the biocatalyst shows sustained chemical synthesis rates for 8 h, paving the way toward a continuous bioprocess. Finally, a sensitivity analysis of cofactor usage revealed that the most expensive cofactors, THF and NADPH, can be reduced by 5-fold without significantly lowering product yields. To the best of our knowledge, this is the first instance of expressing a thermophilic pathway in an E. coli lysate-based CFE system to generate a thermophilic biocatalyst for use at mesophilic temperatures. The CFEbased thermophilic formate-to-serine biocatalyst triples the combined serine and glycine yield previously obtained by a CFE-based mesophilic formate-to-serine biocatalyst (30%), and quadruple the yield obtained by a purified enzyme system (22%). Ultimately, this work opens the door to using E. coli lysate-based CFE for thermophilic biocatalyst generation to achieve high chemical synthesis yields.

bacteria↗
DOE OSTI2025

Retrobiosynthesis of unnatural lactams via reprogrammed polyketide synthase

Engineered polyketide synthases (PKSs) have great potential as biocatalysts. These unnatural enzymes are capable of synthesizing molecules that are either not amenable to biosynthesis or are extremely challenging to access chemically. PKSs can thus be a powerful platform to expand the chemical landscape beyond the limits of conventional metabolic engineering. Here we employ a retrobiosynthesis approach to design and construct PKSs to produce δ-valerolactam (VL) and three enantiopure α-substituted VL analogues that have no known biosynthetic route. We introduce the engineered PKSs and pathways for various malonyl-CoA derivatives into Pseudomonas putida and use proteomics, metabolomics and culture condition optimization to improve the production of our target compounds. These α-substituted VLs are polymerized into polyamides (nylon-5) or converted into their N-acryloyl derivatives. RAFT polymerization produces bio-derived polymers with potential biomedical applications. Overall, this interdisciplinary effort highlights the versatility and effectiveness of a PKS-based retrobiosynthesis approach in exploring and developing innovative biomaterials.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Carrier- and strain-tunable intrinsic magnetism in two-dimensional $MAX_3$ transition metal chalcogenides

Here, we present a density functional theory study of the carrier-density and strain dependence of magnetic order in two-dimensional (2D) $MAX_3$ ($\textit{M}$ = V, Cr, Mn, Fe, Co, Ni; $\textit{A}$ = Si, Ge, Sn; and $\textit{X}$ = S, Se, Te) transition metal trichalcogenides. Our ab initio calculations show that this class of compounds includes wide and narrow gap semiconductors, metals, and half-metals, and that most of these compounds are magnetic. Although antiferromagnetic order is most common, ferromagnetism is predicted in $\textit{M}$SiSe 3 for $\textit{M}$ = Mn and Ni; in $\textit{M}$SiTe 3 for $\textit{M}$ = V and Ni; in MnGeSe 3 ; $\textit{M}$GeTe 3 for $\textit{M}$ = Cr, Mn, and Ni; in FeSnS 3 ; and in MSnTe 3 for $\textit{M}$ = V, Mn, and Fe. Among these compounds CrGeTe 3 , VSnTe 3 , and CrSnTe 3 are ferromagnetic semiconductors. Our calculations suggest that the competition between antiferromagnetic and ferromagnetic order can be substantially altered by strain engineering, and in the semiconductor case also by gating. The associated critical temperatures can be enhanced by means of carrier doping and strains.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2023

Systems Engineering of Rhodococcus opacus to Enable Production of Drop-in Fuels from Lignocellulose

Production of drop-in fuels from lignocellulose using Rhodococcus opacus PD630 (hereafter R. opacus) is a challenging goal. During the grant period we have pushed the field forward significantly in several areas of research. Towards the end goal of accelerating the adoption of R. opacus in biofuel production, during the grant period we have expanded the phenotypic characterization of R. opacus grown in single aromatic (model lignocellulosic) compounds or their mixtures, modeling the growth conditions in lignocellulosic biomass. Harnessing the power of adaptive evolution, we produced evolved R. opacus isolates with superior lignin valorization capabilities and identified differentially expressed genes and pathways after adaptation. We used next generation multi-omic techniques such as genomic, transcriptomic, and metabolomic analyses, to identify the catabolic pathways used by R. opacus to degrade aromatic compounds and funnel these degradation products into central metabolism, as well as the aromatic transport genes required for increased tolerance and utilization. Taking this information one step further, we identified endogenous transcription factors and regulatory mechanisms important for degradation of five model aromatic compounds. To accurately estimate R. opacus growth and consumption on model lignin compounds we pioneered the use of novel extraction procedures prior to GC-MS analysis. Alongside 13 C-metabolic flux analysis, we have elucidated the metabolic routes preferred by Rhodococcus opacus during aromatic compound degradation. Finally, we used in tandem lipidomics and high-resolution mass spectrometry to identify the modulation of mycolic acids and phospholipid membrane composition modification as a strategy for aromatic tolerance in R. opacus. Being a non-model organism, R. opacus lacks the breadth of tools and technical foundation which drive biofuel research in more well-understood microbes such as Escherichia coli. To reduce this burden for use, we designed and produced new tools for genomic manipulation and engineering in R. opacus. These engineering breakthroughs support efficient genomic editing, enabling gene overexpression, repression, and genetic alteration. Using these tools, we have generated synthetically engineered strains with increased lipogenesis and growth, both positive traits required for increased lignin valorization. Optimizing engineered strains for biofuel production from lignocellulose requires extremely sophisticated synthetic rewiring of metabolism. To facilitate systems-level reorganization of metabolism in R. opacus, we created a genome-scale model that accurately predicts metabolic flux and growth rates on the aromatic compound phenol. Lignin requires extensive pre-treatment before biological degradation by R. opacus. Towards an eventual goal of degrading real-world lignin, we developed new depolymerization processes to generate lignin breakdown products (LBP). We optimized LBP storage and composition analysis techniques, enabling accurate prediction of specific LBP compound integration into cell wall components. Overall, through the work funded by this grant we generated 20 manuscripts (17 published, 3 in review/preparation), methods for increased accuracy in metabolomics of aromatic compounds, multiple genetic tools for altering the R. opacus genome, genome scale models for predicting flux through metabolic pathways, as well as multi-omic data for community use. The work funded by this grant has increased the knowledge of aromatic degradation in bacteria and advanced our efforts to optimize R. opacus for lignin valorization.

09 BIOMASS FUELS↗